Bioprinting 3D skin for patient-specific drug discovery in inflammatory skin diseases.

Project Summary Psoriasis is an inflammatory skin disorder with abnormal epidermal hyperproliferation, which affects 2-3 % of the US population. There are no reliable in vitro models with which the efficacy and safety of psoriasis drug candidates can be tested. To meet this major unmet pharmaceutical need, we will combine iPSC reprograming and 3D bioprinting technologies to construct a 3D skin model to screen for drugs to treat this disease. iPSC methodology will be used, because iPSCs have unlimited proliferation potential and the capability to differentiate into different cell lineages, which allows us to circumvent the limitation imposed by the limited availability of primary cells that can be procured from patients. We successfully constructed 3D skin using exclusively iPSC-derived cells (fibroblasts and keratinocytes), demonstrating the feasibility of this approach. 3D bioprinting can allow us to reproducibly construct complex structures to recapitulate human tissues/organs. In this project, we will first construct immunocompetent 3D skin with primary keratinocytes, fibroblasts and T cells. Then, iPSCs will be reprogramed from fibroblasts or blood cells obtained from normal and psoriatic individuals. Keratinocytes and fibroblasts will be differentiated from iPSCs for construction of 3D skin models, whereas the abundant availability of T cells allows us to use cells directly from primary sources. Bioprinted psoriasis-specific iPSC derived skin constructs will be used for disease modeling and pharmacological validation. CRISPR technology will be used to integrate fluorescent reporters in iPSC-derived keratinocytes to monitor disease induction of psoriasis and effect of drug treatment. Completion of this project will provide us with a reliable 3D bioprinted model to develop drugs to treat psoriasis. Moreover, our 3D skin model can be easily adapted and modified to screen for drugs to treat other skin diseases, using a platform approach.